Analysis of Arctic and Antarctic sea ice extent using quantile regression
Abstract A number of recent studies have examined trends in sea ice cover using ordinary least squares regression. In this study, quantile regression is applied to analyse other aspects of the distribution of sea ice extent. More specifically, trends in the mean, maximum, and minimum sea ice extent...
| Published in: | International Journal of Climatology |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2012
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1002/joc.3491 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.3491 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.3491 |
| Summary: | Abstract A number of recent studies have examined trends in sea ice cover using ordinary least squares regression. In this study, quantile regression is applied to analyse other aspects of the distribution of sea ice extent. More specifically, trends in the mean, maximum, and minimum sea ice extent in the Arctic and Antarctic are investigated. While there is a significant decreasing trend in mean Arctic sea ice extent of − 4.5% per decade from 1979 through 2010, the Antarctic results show a small positive trend of 2.3% per decade. In some cases such as the Antarctic minimum ice cover, selected quantile regressions yield slope estimates that differ from trends in the mean. It was also found that the variability in Antarctic sea ice extent is higher than that in the Arctic. Copyright © 2012 Royal Meteorological Society |
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